Instructions to use Mathnub/imdb-score-predict-distilbert2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathnub/imdb-score-predict-distilbert2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mathnub/imdb-score-predict-distilbert2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mathnub/imdb-score-predict-distilbert2") model = AutoModelForSequenceClassification.from_pretrained("Mathnub/imdb-score-predict-distilbert2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mathnub/imdb-score-predict-distilbert2: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Mathnub/imdb-score-predict-distilbert2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mathnub/imdb-score-predict-distilbert2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mathnub/imdb-score-predict-distilbert2/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 5ce3217edf2e79ac97cbef16e031f76d99c9bb6bcd80735dbcb80197c4724a72
- Size of remote file:
- 268 MB
- SHA256:
- 6df877f9af9ee5a982e279c251b631134b5380f405e693eaba316eaf63052599
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